Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 645 410 673 713 728 652 654 511 573 691 507 535 419 558 861 837 836 493 965 249
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] 861 728 NA 652 419 511 558 837 673 965 493 654 573 535 645 NA 410 836 NA 691 507 713 249
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 3 4 2 2 3 2 4 4 5 2
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y"
[26] "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y"
[26] "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "o" "f" "q" "i" "t" "S" "Z" "O" "K" "Q"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
[1] 19
which( manyNumbersWithNA > 900 )
[1] 10
which( is.na( manyNumbersWithNA ) )
[1] 3 16 19
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
[1] 965
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
[1] 965
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
[1] 965
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "S" "Z" "O" "K" "Q"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "o" "f" "q" "i" "t"
manyNumbers %in% 300:600
[1] FALSE TRUE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE FALSE FALSE FALSE
[18] TRUE FALSE FALSE
which( manyNumbers %in% 300:600 )
[1] 2 8 9 11 12 13 14 18
sum( manyNumbers %in% 300:600 )
[1] 8
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] "large" "large" NA "large" "small" "large" "large" "large" "large" "large" "small" "large"
[13] "large" "large" "large" NA "small" "large" NA "large" "large" "large" "small"
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "large" "large" "UNKNOWN" "large" "small" "large" "large" "large" "large" "large"
[11] "small" "large" "large" "large" "large" "UNKNOWN" "small" "large" "UNKNOWN" "large"
[21] "large" "large" "small"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] 861 728 NA 652 0 511 558 837 673 965 0 654 573 535 645 NA 0 836 NA 691 507 713 0
unique( duplicatedNumbers )
[1] 3 4 2 5
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 3 4 2 5
duplicated( duplicatedNumbers )
[1] FALSE FALSE FALSE TRUE TRUE TRUE TRUE TRUE FALSE TRUE
which.max( manyNumbersWithNA )
[1] 10
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 965
which.min( manyNumbersWithNA )
[1] 23
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 249
range( manyNumbersWithNA, na.rm = TRUE )
[1] 249 965
manyNumbersWithNA
[1] 861 728 NA 652 419 511 558 837 673 965 493 654 573 535 645 NA 410 836 NA 691 507 713 249
sort( manyNumbersWithNA )
[1] 249 410 419 493 507 511 535 558 573 645 652 654 673 691 713 728 836 837 861 965
sort( manyNumbersWithNA, na.last = TRUE )
[1] 249 410 419 493 507 511 535 558 573 645 652 654 673 691 713 728 836 837 861 965 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 965 861 837 836 728 713 691 673 654 652 645 573 558 535 511 507 493 419 410 249 NA NA NA
manyNumbersWithNA[1:5]
[1] 861 728 NA 652 419
order( manyNumbersWithNA[1:5] )
[1] 5 4 2 1 3
rank( manyNumbersWithNA[1:5] )
[1] 4 3 5 2 1
sort( mixedLetters )
[1] "f" "i" "K" "o" "O" "q" "Q" "S" "t" "Z"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 4.0 7.5 2.0 7.5 5.0 2.0 2.0 7.5 10.0 7.5
rank( manyDuplicates, ties.method = "min" )
[1] 4 6 1 6 5 1 1 6 10 6
rank( manyDuplicates, ties.method = "random" )
[1] 4 7 2 6 5 3 1 9 10 8
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.00000000 -0.50000000 0.00000000 0.50000000 1.00000000 -0.75598051 0.04192044 1.28736653
[9] 0.53801260 0.66749581 0.63383308 -1.05891116 0.62195381 -0.33191859 0.45806834
round( v, 0 )
[1] -1 0 0 0 1 -1 0 1 1 1 1 -1 1 0 0
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 -0.8 0.0 1.3 0.5 0.7 0.6 -1.1 0.6 -0.3 0.5
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 -0.76 0.04 1.29 0.54 0.67 0.63 -1.06 0.62 -0.33 0.46
floor( v )
[1] -1 -1 0 0 1 -1 0 1 0 0 0 -2 0 -1 0
ceiling( v )
[1] -1 0 0 1 1 0 1 2 1 1 1 -1 1 0 1
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 x 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
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